ArticleBMC genomics2014
Transcriptome structure variability in Saccharomyces cerevisiae strains determined with a newly developed assembly software.
Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- Designing RNA sequencing experiments: A practical guide to reproducible gene expression analysis.Computational and structural biotechnology journal · 2026Review
- New insights into genome annotation in Podospora anserina through re-exploiting multiple RNA-seq data.BMC genomics · 2022Article
- Comparative Transcriptomic Analysis ofFrontiers in microbiology · 2018Article
- Similarity-Based Segmentation of Multi-Dimensional Signals.Scientific reports · 2017Article
- Omics analysis of acetic acid tolerance in Saccharomyces cerevisiae.World journal of microbiology & biotechnology · 2017Review
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRNA-seq studies have an important role for both large-scale analysis of gene expression and for transcriptome reconstruction. However, the lack of software specifically developed for the analysis of the transcriptome structure in lower eukaryotes, has so far limited the comparative studies among different species and strains.
resultsIn order to fill this gap, an innovative software called ORA (Overlapped Reads Assembler) was developed. This software allows a simple and reliable analysis of the transcriptome structure in organisms with a low number of introns. It can also determine the size and the position of the untranslated regions (UTR) and of polycistronic transcripts. As a case study, we analyzed the transcriptional landscape of six S. cerevisiae strains in two different key steps of the fermentation process. This comparative analysis revealed differences in the UTR regions of transcripts. By extending the transcriptome analysis to yeast species belonging to the Saccharomyces genus, it was possible to examine the conservation level of unknown non-coding RNAs and their putative functional role.
conclusionsBy comparing the results obtained using ORA with previous studies and with the transcriptome structure determined with other software, it was proven that ORA has a remarkable reliability. The results obtained from the training set made it possible to detect the presence of transcripts with variable UTRs between S. cerevisiae strains. Finally, we propose a regulatory role for some non-coding transcripts conserved within the Saccharomyces genus and localized in the antisense strand to genes involved in meiosis and cell wall biosynthesis.
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